Notes on Music Information Retrieval
¶
Register for the 2017 Summer Workshop on MIR at CCRMA, Stanford!
Introduction
¶
About This Site
(
ipynb
) Start here!
What is MIR?
(
ipynb
)
Overview of a Basic MIR System
(
ipynb
)
Python Basics
(
ipynb
)
Getting Good at IPython
(
ipynb
)
Using Audio in IPython
(
ipynb
)
NumPy and SciPy Basics
(
ipynb
)
Music Representations
¶
Sheet Music Representations
(
ipynb
)
Symbolic Representations
(
ipynb
)
Audio Representation
(
ipynb
)
Tuning Systems
(
ipynb
)
Exercise: Understanding Audio Features through Sonification
(
ipynb
)
Signal Analysis and Feature Extraction
¶
Basic Feature Extraction
(
ipynb
)
Segmentation
(
ipynb
)
Zero Crossing Rate
(
ipynb
)
Fourier Transform
(
ipynb
)
Short-Time Fourier Transform
(
ipynb
)
Spectral Features
(
ipynb
)
Pitch Transcription Exercise
(
ipynb
)
Machine Learning
¶
K-Nearest Neighbor Classification
(
ipynb
)
Cross Validation
(
ipynb
)
Exercise: K-Nearest Neighbor Instrument Classification
(
ipynb
)
K-Means Clustering
(
ipynb
)
Exercise: Unsupervised Instrument Classification using K-Means
(
ipynb
)
Neural Networks
(
ipynb
)
Evaluation
(
ipynb
)
Genre Recognition
(
ipynb
)
Exercise: Genre Recognition
(
ipynb
)
Music Synchronization
¶
Dynamic Time Warping
(
ipynb
)
Music Structure Analysis
¶
Mel-Frequency Cepstral Coefficients
(
ipynb
)
Rhythm, Tempo, and Beat Tracking
¶
Onset Detection
(
ipynb
)
Tempo Estimation
(
ipynb
)
Autocorrelation
(
ipynb
)
Beat Tracking
(
ipynb
)
Drum Transcription using ADTLib
(
ipynb
)
Content-Based Audio Retrieval
¶
Locality Sensitive Hashing
(
ipynb
)
Musically Informed Audio Decomposition
¶
Principal Component Analysis
(
ipynb
)
Nonnegative Matrix Factorization
(
ipynb
)
Harmonic-Percussive Source Separation
(
ipynb
)
Exercise: Source Separation using NMF
(
ipynb
)
Classification of Separated Signals
Appendix
¶
Beat Tracking in Essentia
(
ipynb
)
Spectral Features in Essentia
(
ipynb
)
Feature Extraction in Essentia
(
ipynb
)